diff --git a/R/qc_sequence_coverage.R b/R/qc_sequence_coverage.R
index 2652a274..48b5b9ce 100644
--- a/R/qc_sequence_coverage.R
+++ b/R/qc_sequence_coverage.R
@@ -49,10 +49,10 @@ qc_sequence_coverage <- function(data,
                                  interactive = FALSE) {
 
   # Validate inputs
-  if (!all(c({{ protein_identifier }},{{ coverage }}) %in% colnames(data))) {
+  if (!all(c(rlang::as_name(rlang::enquo(protein_identifier)), rlang::as_name(rlang::enquo(coverage))) %in% colnames(data))) {
     stop("Column names for protein_identifier and coverage must exist in the dataset.")
   }
-  
+
   result <- data %>%
     dplyr::distinct({{ protein_identifier }}, {{ coverage }}, {{ sample }}) %>%
     tidyr::drop_na({{ coverage }}) %>%
@@ -77,7 +77,7 @@ qc_sequence_coverage <- function(data,
       size = 1
     ) +
     ggplot2::geom_vline(data = result %>% dplyr::distinct(.data$median_coverage, {{ sample }}),
-                        mapping = aes(xintercept = median_coverage),
+                        mapping = aes(xintercept = .data$median_coverage),
                         linewidth = 1,
                         linetype = "dashed") +
     ggplot2::labs(
diff --git a/man/normalise.Rd b/man/normalise.Rd
index 7e1f49b8..568b446f 100644
--- a/man/normalise.Rd
+++ b/man/normalise.Rd
@@ -7,7 +7,8 @@
 normalise(data, sample, intensity_log2, method = "median")
 }
 \arguments{
-\item{data}{a data frame containing at least sample names and intensity values.}
+\item{data}{a data frame containing at least sample names and intensity values. Please note that if the
+data frame is grouped, the normalisation will be computed by group.}
 
 \item{sample}{a character column in the \code{data} data frame that contains the sample names.}
 
diff --git a/man/qc_sequence_coverage.Rd b/man/qc_sequence_coverage.Rd
index 05188fba..c8f4d516 100644
--- a/man/qc_sequence_coverage.Rd
+++ b/man/qc_sequence_coverage.Rd
@@ -21,7 +21,7 @@ identifiers.}
 \item{coverage}{a numeric column in the \code{data} data frame that contains protein coverage
 in percent. This information can be obtained using the \code{\link{sequence_coverage}} function.}
 
-\item{sample}{optional, a character column in the \code{data} data frame that contains sample names.
+\item{sample}{optional, a character or factor column in the \code{data} data frame that contains sample names.
 Please only provide this argument if you want to facet the distribution plot by sample
 otherwise do not provide this argument.}